IGF-1 rs6218 polymorphisms modulate the susceptibility to age-related cataract.

Background: Single nucleotide polymorphisms (SNPs), as the most abundant form of DNA variation in the human genome, contribute to age-related cataracts (ARC) development. Apoptosis of lens epithelial cells (LECs) is closely related to ARC formation. Insulin-like growth factor 1 (IGF1) contributes to cell apoptosis regulation. Moreover, IGF1 was indicated to exhibit a close association with cataract formation. Afterward, an investigation was conducted to examine the correlation between polymorphisms in IGF1 and the susceptibility to ARC. Methods: The present investigation was a case-control study. Venous blood draws were collected from the participants for DNA genotyping. Lens capsule samples were collected to detect mRNA and apoptosis. TaqMan RT-PCR was used to detect IGF1 polymorphism genotypes and qRT PCR was used to detect IGF1 mRNA levels in LECs. LEC apoptosis was evaluated through flow cytometry. The chi-square test was used to compare differences between ARCs and controls of each SNP. Results: We found that the G allele frequency in the IGF1-rs6218 was higher in the ARCs than in the controls. Furthermore, it was observed that the rs6218 GG genotype exhibited a positive correlation to elevated levels of IGF1 mRNA in LECs. The IGF1 mRNA in the LECs and the apoptosis of LECs in nuclear type of ARCs (ARNC) was higher than the controls. Conclusion: The susceptibility to ARC was related to IGF1-rs6218 polymorphism, and this polymorphism is associated with IGF1 expression at the mRNA level. Moreover, apoptosis in LECs of ARNCs was found to be increased.

The association of FSCN1 (rs852479, rs1640233) and HOTAIR (rs920778) polymorphisms with the risk of breast cancer in Egyptian women.

BACKGROUND: Breast cancer (BC) is one of the most prevalent cancers that contribute to mortality among women worldwide. Despite contradictory findings, considerable evidence suggests that single nucleotide polymorphisms (SNPs) in the FSCN1 and HOTAIR genes may have a causative impact on the development of BC. This case-control study was conducted to evaluate the association of genotype frequency in FSCN1 rs852479, rs1640233, and HOTAIR rs920778 with susceptibility and prognosis of BC, as well as the impact of clinical stages and hormonal features. METHODS AND RESULTS: FSCN1 (rs852479, rs1640233) and HOTAIR (rs920778) were genotyped using TaqMan real-time PCR assay in 200 BC patients and 200 cancer-free controls, all representing Egyptian women. Genotypic analyses in association with clinicopathological factors and disease risk were assessed. As a result, a significant association with BC risk was observed for CC genotype frequency of FSCN1 rs852479 A > C (OR = 0.395, 95% CI 0.204-0.76, p-value = 0.005). However, no significant correlation was detected between the FSCN1 rs1640233 C > T and HOTAIR rs920778 C > T polymorphic variants and susceptibility to BC. Interestingly, CC genotype of FSCN1 rs1640233 was more likely to progress tumor size and lymph node invasion in BC cases (p-value = 0.04 and 0.02, respectively). Moreover, it was revealed that there was a non-significant correlation between the haplotype distributions of FSCN1 rs852479 and rs1640233 and the probability of BC. CONCLUSIONS: Based on the sample size and genetic characteristics of the subjects involved in the present study, our findings indicated that FSCN1 rs852479 may contribute to BC susceptibility in a sample of the Egyptian population.

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases.

BACKGROUND: Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD. METHODS: Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets. RESULTS: Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure. CONCLUSIONS: This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Dual toeholds regulated CRISPR-Cas12a sensing platform for ApoE single nucleotide polymorphisms genotyping.

Single nucleotide polymorphisms (SNPs) are closely associated with many biological processes, including genetic disease, tumorigenesis, and drug metabolism. Accurate and efficient SNP determination has been proved pivotal in pharmacogenomics and diagnostics. Herein, a universal and high-fidelity genotyping platform is established based on the dual toeholds regulated Cas12a sensing methodology. Different from the conventional single stranded or double stranded activation mode, the dual toeholds regulated mode overcomes protospacer adjacent motif (PAM) limitation via cascade toehold mediated strand displacement reaction, which is highly universal and ultra-specific. To enhance the sensitivity for biological samples analysis, a modified isothermal recombinant polymerase amplification (RPA) strategy is developed via utilizing deoxythymidine substituted primer and uracil-DNA glycosylase (UDG) treatment, designated as RPA-UDG. The dsDNA products containing single stranded toehold domain generated in the RPA-UDG allow further incorporation with dual toeholds regulated Cas12a platform for high-fidelity human sample genotyping. We discriminate all the single-nucleotide polymorphisms of ApoE gene at rs429358 and rs7412 loci with human buccal swab samples with 100% accuracy. Furthermore, we engineer visual readout of genotyping results by exploiting commercial lateral flow strips, which opens new possibilities for field deployable implementation.

Interpreting population- and family-based genome-wide association studies in the presence of confounding.

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the "indirect" genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.

Delving the vitamin D receptor variation and expression profiles in the context of type 2 diabetes among families.

BACKGROUND: Vitamin D is essential for insulin secretion and sensitivity. Consequently, its inadequacy is linked to higher insulin resistance and Type 2 Diabetes (T2D). The Vitamin D receptor (VDR) gene is one potential candidate for T2D, and multiple polymorphisms in VDR have been examined in various populations, but no conclusive answers have been provided. OBJECTIVES: This study was designed to evaluate the susceptibility of VDR gene polymorphism and its expression in diabetic families in Pakistan. METHODOLOGY: In this family-based study, twenty diabetic families with a positive family history of T2D and at least three T2D patients were recruited from outpatient clinics and public hospitals. The current study comprised 143 individuals with 55 affected and 88 unaffected individuals. Blood samples of the selected families were collected. DNA was extracted from the collected samples and the PCR-RFLP method was followed to identify the genotyping and RT-qPCR for expression. Phenotypic and genotypic pedigrees of the families were developed by the progeny online tool. The association values of SNPs were determined by TDT and DFAM analysis implemented on Plink software. RESULTS: The results explained a significant familial aggregation among phenotypic characters including Age, Gender, BMI (body mass index), age of disease diagnosis, disease duration, and blood pressure in the probands, affected FDRs (First Degree Relatives) and affected SDRs (Second Degree Relatives). A significant association of rs731236 C/T (OR = 1.522), rs2228570 C/T (OR = 1.327) with p < 0.05. Whereas, for rs1544410 G/A (OR = 0.9706) and rs7975232 T/G (OR = 0.7368) no considerable association evidence was seen (p > 0.05) in families. The mRNA expression of VDR increased threefold (p = 0.0204) in patients compared to controls. Variation-based expression analysis exhibited that the rs2228570 genotype influences the expression. CONCLUSION: A linkage was found among the FDRs with probands. Variation in the gene VDR at loci rs731236 and rs2228570 was associated with familial T2D. However further research is required to explore more genetic factors that could influence T2D risks in families.

Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia.

BACKGROUND: Numerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies. METHODS: We utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein-protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets. RESULTS: We found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data. CONCLUSIONS: Our study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.

KASP: a high-throughput genotyping system and its applications in major crop plants for biotic and abiotic stress tolerance.

Advances in plant molecular breeding have resulted in the development of new varieties with superior traits, thus improving the crop germplasm. Breeders can screen a large number of accessions without rigorous and time-consuming phenotyping by marker-assisted selection (MAS). Molecular markers are one of the most imperative tools in plant breeding programmes for MAS to develop new cultivars possessing multiple superior traits. Single nucleotide polymorphisms (SNPs) are ideal for MAS due to their low cost, low genotyping error rates, and reproducibility. Kompetitive Allele Specific PCR (KASP) is a globally recognized technology for SNP genotyping. KASP is an allele-specific oligo extension-based PCR assay that uses fluorescence resonance energy transfer (FRET) to detect genetic variations such as SNPs and insertions/deletions (InDels) at a specific locus. Additionally, KASP allows greater flexibility in assay design, which leads to a higher success rate and the capability to genotype a large population. Its versatility and ease of use make it a valuable tool in various fields, including genetics, agriculture, and medical research. KASP has been extensively used in various plant-breeding applications, such as the identification of germplasm resources, quality control (QC) analysis, allele mining, linkage mapping, quantitative trait locus (QTL) mapping, genetic map construction, trait-specific marker development, and MAS. This review provides an overview of the KASP assay and emphasizes its validation in crop improvement related to various biotic and abiotic stress tolerance and quality traits.

The effects of ANRIL polymorphisms on colorectal cancer, tumor stage, and tumor grade among Iranian population.

BACKGROUND: Colorectal cancer (CRC) is a type of neoplasm, developing in the colon or rectum. The exact etiology of CRC is not well known, but the role of genetic, epigenetic, and environmental factors are established in its pathogenesis. Therefore, the aim of this research was to explore the effects of ANRIL polymorphisms on the CRC and its clinical findings. METHODS AND RESULTS: The peripheral blood specimens were collected from 142 CRC patients and 225 controls referred to Milad Hospital, Tehran, Iran. PCR- RFLP method was used to analyze ANRIL rs1333040, rs10757274 rs4977574, and rs1333048 polymorphisms. The ANRIL rs1333040 polymorphism was related to a higher risk of CRC in the co-dominant, dominant, and log-additive models. ANRIL rs10757274, rs4977574, and rs1333048 polymorphisms showed no effect on CRC susceptibility. The CGAA and TGGA haplotypes of ANRIL rs1333040/ rs10757274/ rs4977574/rs1333048 polymorphisms were associated with the higher and the lower risk of CRC respectively. The rs1333040 polymorphism was associated with higher TNM stages (III and IV). The frequency of ANRIL rs10757274 polymorphism was lower in CRC patients over 50 years of age only in the dominant model. In addition, the rs10757274 was associated with well differentiation in CRC patients. CONCLUSION: The ANRIL rs1333040 polymorphism was associated with a higher risk of CRC and higher TNM stages. ANRIL rs10757274 polymorphism was associated with the well-differentiated tumor in CRC.

Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.).

BACKGROUND: This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS). RESULTS: The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64-32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis. CONCLUSIONS: Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies. METHODS: This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications. RESULTS: We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets. CONCLUSIONS: Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

Genetic diversity of Mycobacterium leprae: Need to move towards genome-wide approaches.

ABSTRACT: Leprosy, an ancient disease, continues to be a public health concern as it remains endemic in several countries. After reaching the elimination target (1/10,000) as a public health problem in 2005 in India, around 1.2 lakh cases have been detected every year over the last decade indicating active transmission of leprosy bacillus (Mycobacterium leprae). Single-nucleotide polymorphisms (SNPs), genomic insertions/deletions and variable-number tandem repeats (VNTRs) have been identified as genetic markers for tracking M. leprae transmission. As the leprosy bacilli cannot be cultured in vitro, molecular testing of M. leprae genotypes is done by polymerase chain reaction-based sequencing which provides a practical alternative for the identification of strains as well as drug resistance-associated mutations. Whole-genome sequencing (WGS) of M. leprae directly from clinical samples has also proven to be an effective tool for identifying genetic variations which can further help refine the molecular epidemiological schemes based on SNPs and VNTRs. However, the WGS data of M. leprae strains from India are scarce, being responsible for a gross under-representation of the genetic diversity of M. leprae strains present in India and need to be addressed suitably. Molecular studies of leprosy can provide better insight into phylogeographic markers to monitor the transmission dynamics and emergence of antimicrobial resistance. An improved understanding of M. leprae transmission is essential to guide efficient leprosy control strategies. Therefore, this review compiles and discusses the current status of molecular epidemiology, genotyping and the potential of genome-wide analysis of M. leprae strains in the Indian context.

Periodontitis and osteoporosis: a two-sample Mendelian randomization analysis.

The incidences of periodontitis and osteoporosis are rising worldwide. Observational studies have shown that periodontitis is associated with increased risk of osteoporosis. We performed a Mendelian randomization (MR) study to genetically investigate the causality of periodontitis on osteoporosis. We explored the causal effect of periodontitis on osteoporosis by MR analysis. A total of 9 single nucleotide polymorphisms (SNP) were related to periodontitis. The primary approach in this MR analysis was the inverse variance-weighted (IVW) method. Simple median, weighted median, and penalized weighted median were used to analyze sensitivity. The fixed-effect IVW model and random-effect IVW model showed no significant causal effect of genetically predicted periodontitis on the risk of osteoporosis (OR=1.032; 95%CI: 0.923-1.153; P=0.574; OR=1.032; 95%CI: 0.920-1.158; P=0.588, respectively). Similar results were observed in simple mode (OR=1.031; 95%CI: 0.780-1.361, P=0.835), weighted mode (OR=1.120; 95%CI: 0.944-1.328, P=0.229), simple median (OR=1.003; 95%CI: 0.839-1.197, P=0.977), weighted median (OR=1.078; 95%CI: 0.921-1.262, P=0.346), penalized weight median (OR 1.078; 95%CI: 0.919-1.264, P=0.351), and MR-Egger method (OR=1.360; 95%CI: 0.998-1.853, P=0.092). There was no heterogeneity in the IVW and MR-Egger analyses (Q=7.454, P=0.489 and Q=3.901, P=0.791, respectively). MR-Egger regression revealed no evidence of a pleiotropic influence through genetic variants (intercept: -0.004; P=0.101). The leave-one-out sensitivity analysis indicated no driven influence of any individual SNP on the association between periodontitis and osteoporosis. The Mendelian randomization analysis did not show a significant detrimental effect of periodontitis on the risk of osteoporosis.

Development of a high-density sub-species-specific targeted SNP assay for Rocky Mountain bighorn sheep (Ovis canadensis canadensis).

Due to their abundance and relative ease of genotyping, single nucleotide polymorphisms (SNPs) are a commonly used molecular marker for contemporary population genetic and genomic studies. A high-density and cost-effective way to type SNP loci is Allegro targeted genotyping (ATG), which is a form of targeted genotyping by sequencing developed and offered by Tecan genomics. One major drawback of this technology is the need for a reference genome and information on SNP loci when designing a SNP assay. However, for some non-model species genomic information from other closely related species can be used. Here we describe our process of developing an ATG assay to target 50,000 SNPs in Rocky Mountain bighorn sheep, using a reference genome from domestic sheep and SNP resources from prior bighorn sheep studies. We successfully developed a high accuracy, high-density, and relatively low-cost SNP assay for genotyping Rocky Mountain bighorn sheep that genotyped ~45,000 SNP loci. These loci were relatively evenly distributed throughout the genome. Furthermore, the assay produced genotypes at tens of thousands of SNP loci when tested on other mountain sheep species and subspecies.

Association of a single-nucleotide polymorphism in C12orf43 region with the risk of coronary artery disease.

The genetics of organisms play a vital role in the development of coronary artery disease (CAD), with its heritability estimated at approximately 50-60%. For this purpose, we examined the relationship between CAD risk and C12orf43/rs2258287 polymorphisms in the Pakistani population. In this study based on the genetic approach to dyslipidemia, a total of 200 subjects were included from the southern Punjab. The biochemical analysis of parameters (total cholesterol, triglycerides, blood glucose, high-density lipoprotein, and low-density lipoprotein) was carried out along with molecular analysis using an ARMS-PCR-based assay for single-nucleotide polymorphism (SNP) C12orf43/rs2258287 to identify the genotype. Genotypes showed a substantial correlation with both family history and metabolic markers. The cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides and blood glucose levels were higher while the high-density lipoprotein cholesterol (HDL-C) level was lower significantly (p<0.05) in cases than in controls. Age, pulse rate, diabetes, physical activity, smoking, family history, and dietary habits were also significantly associated (p<0.05) with CAD individuals. The SNP C12orf43/rs2258287 also showed an association with CAD in the population of southern Punjab. Based upon this study, it could be concluded that CAD is characterized by an unfavorable lipid profile in association with SNP C12orf43/rs2258287.

A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis.

BACKGROUND: 'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056). RESULTS: We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null. CONCLUSION: Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.

Association of Polymorphic Variants of TCF7L2 and PPARG Genes with Metabolic Markers in Patients with Early Disorders of Carbohydrate Metabolism.

We performed complex analysis of the association of polymorphic variants rs7903146 of the TCF7L2 gene and rs1801282 of the PPARG gene with metabolic parameters, insulin resistance, and ß-cell function in a group of patients with early signs of carbohydrate metabolism disturbances in a sample of Tyumen citizens. The study group consisted of 64 people (39 women, 25 men) aged 40-70 years. The distribution of frequencies of alleles and genotypes of the polymorphic markers rs7903146 and rs1801282 was analyzed and associations of carriage of major homozygous polymorphisms with various phenotypic traits were identified. Genotyping for polymorphic variants of TCF7L2 and PPARG genes was performed using allele-specific PCR with primers provided by Synthol company. Carriers of homozygotes for allele C of the polymorphic marker rs7903146 significantly differed from other respondents by a higher level of C-peptide, as well as by the presence of associations with waist circumference, elevated level of glycated hemoglobin, and arterial hypertension. Carriers of homozygotes for the allele C of the rs1801282 polymorphism of the PPARG gene differed from the group of carriers of homozygotes for the allele G and the group of heterozygote carriers by higher levels of triglycerides, as well as the presence of associations with waist circumference and the level of glycated hemoglobin.

DHEA and response to antidepressant treatment: A Mendelian Randomization analysis.

Treatment response is hard to predict and detailed mechanisms unknown. Lower levels of the dehydroepiandrosterone sulphate (DHEA(S)) - a precursor to testosterone and estrogen - have been associated to depression and to response to antidepressant treatment. Previous studies however may have been ridden by confounding and reverse causation. The aim of this study is to evaluate whether higher levels of DHEA(S) are causally linked to response to antidepressants using mendelian randomization (MR). We performed a Two-sample MR analysis using data the largest publicly available GWAS of DHEA(S) levels (n = 14,846) using eight common genetic variants associated to DHEA(S) (seven single nucleotide polymorphisms and one variant rs2497306) and the largest GWAS of antidepressant response (n = 5218) using various MR methods (IVW, MR Egger, Weighted mean, weighted mode, MR-PRESSO) and single SNP analysis. We further investigated for pleiotropy conducting a look up on PhenoScanner and GWAS Catalog. Results show no evidence for DHEA(S) gene risk score from any of MR methods, however, we found a significant association on individual variant analysis for rs11761538, rs17277546, and rs2497306. There was some evidence for heterogeneity and pleiotropy. This is the first paper to show some evidence for a causal association of genetically-predicted DHEA and improvement of depressive symptoms. The effect is not a simple linear effect, and we were unable to dissect whether the effect was direct effect of DHEA(S), mediated by DHEA(S) or on the pathway is not yet clear. Further studies using more refined instrumental variables will help clarify this association.

Decoding Non-coding Variants: Recent Approaches to Studying Their Role in Gene Regulation and Human Diseases.

Genome-wide association studies (GWAS) have mapped over 90% of disease- and quantitative-trait-associated variants within the non-coding genome. Non-coding regulatory DNA (e.g., promoters and enhancers) and RNA (e.g., 5' and 3' UTRs and splice sites) are essential in regulating temporal and tissue-specific gene expressions. Non-coding variants can potentially impact the phenotype of an organism by altering the molecular recognition of the cis-regulatory elements, leading to gene dysregulation. However, determining causality between non-coding variants, gene regulation, and human disease has remained challenging. Experimental and computational methods have been developed to understand the molecular mechanism involved in non-coding variant interference at the transcriptional and post-transcriptional levels. This review discusses recent approaches to evaluating disease-associated single-nucleotide variants (SNVs) and determines their impact on transcription factor (TF) binding, gene expression, chromatin conformation, post-transcriptional regulation, and translation.

Determination of IL-6 Gene Promoter Polymorphism in Patients with Hepatitis C and Its Impact on RNA Secondary Structure.

Background and Objectives: A polymorphism in the promoter region of the IL-6 gene would influence the level of IL-6 expression in patients with HCV, resulting in a pro-inflammatory response. Few studies have shown the association between -174G>C (rs1800795) and -1363G>T (rs2069827) polymorphisms and HCV infection, and their results have been contradictory. There are no data published in our population to study such an IL-6 stimulus against HCV infection and its impact on RNA secondary structure. Therefore, we isolated human subjects from the province of Punjab, Pakistan. The objective was to screen for IL-6 gene promoter polymorphisms -174G/C and -1363G/T and those correlated with serum concentrations of IL-6 in patients with HCV and compared with a control. Materials and Methods: In conventional PCR, measurement of serum IL-6 by CLIA and statistical analysis were performed to observe the genotype association studies. By integrating bioinformatics and computational tools, our study aimed to provide a comprehensive understanding of how variations in the promoter region of IL-6 may have functional implications on gene expression. Results: The -174G>C and -1363G>T genotypes in the promoter region of patients with HCV were in strong allelic association (Δ = 0.97, p < 0.001). Interestingly, the bioinformatics analysis was well aligned with our experimental data. Conclusions: Based on the data, it can be inferred that IL-6 gene promoter polymorphisms are important in the dysregulation of IL-6 levels in patients with HCV.